On Controllability of AI
- URL: http://arxiv.org/abs/2008.04071v1
- Date: Sun, 19 Jul 2020 02:49:41 GMT
- Title: On Controllability of AI
- Authors: Roman V. Yampolskiy
- Abstract summary: We present arguments as well as supporting evidence indicating that advanced AI can't be fully controlled.
Consequences of uncontrollability of AI are discussed with respect to future of humanity and research on AI, and AI safety and security.
- Score: 1.370633147306388
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Invention of artificial general intelligence is predicted to cause a shift in
the trajectory of human civilization. In order to reap the benefits and avoid
pitfalls of such powerful technology it is important to be able to control it.
However, possibility of controlling artificial general intelligence and its
more advanced version, superintelligence, has not been formally established. In
this paper, we present arguments as well as supporting evidence from multiple
domains indicating that advanced AI can't be fully controlled. Consequences of
uncontrollability of AI are discussed with respect to future of humanity and
research on AI, and AI safety and security.
Related papers
- Imagining and building wise machines: The centrality of AI metacognition [78.76893632793497]
We argue that shortcomings stem from one overarching failure: AI systems lack wisdom.
While AI research has focused on task-level strategies, metacognition is underdeveloped in AI systems.
We propose that integrating metacognitive capabilities into AI systems is crucial for enhancing their robustness, explainability, cooperation, and safety.
arXiv Detail & Related papers (2024-11-04T18:10:10Z) - On the consistent reasoning paradox of intelligence and optimal trust in AI: The power of 'I don't know' [79.69412622010249]
Consistent reasoning, which lies at the core of human intelligence, is the ability to handle tasks that are equivalent.
CRP asserts that consistent reasoning implies fallibility -- in particular, human-like intelligence in AI necessarily comes with human-like fallibility.
arXiv Detail & Related papers (2024-08-05T10:06:53Z) - Artificial Intelligence: Arguments for Catastrophic Risk [0.0]
We review two influential arguments purporting to show how AI could pose catastrophic risks.
The first argument -- the Problem of Power-Seeking -- claims that advanced AI systems are likely to engage in dangerous power-seeking behavior.
The second argument claims that the development of human-level AI will unlock rapid further progress.
arXiv Detail & Related papers (2024-01-27T19:34:13Z) - Close the Gates: How we can keep the future human by choosing not to develop superhuman general-purpose artificial intelligence [0.20919309330073077]
In the coming years, humanity may irreversibly cross a threshold by creating general-purpose AI.
This would upend core aspects of human society, present many unprecedented risks, and is likely to be uncontrollable in several senses.
We can choose to not do so, starting by instituting hard limits on the computation that can be used to train and run neural networks.
With these limits in place, AI research and industry can focus on making both narrow and general-purpose AI that humans can understand and control, and from which we can reap enormous benefit.
arXiv Detail & Related papers (2023-11-15T23:41:12Z) - Managing extreme AI risks amid rapid progress [171.05448842016125]
We describe risks that include large-scale social harms, malicious uses, and irreversible loss of human control over autonomous AI systems.
There is a lack of consensus about how exactly such risks arise, and how to manage them.
Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness, and barely address autonomous systems.
arXiv Detail & Related papers (2023-10-26T17:59:06Z) - Fairness in AI and Its Long-Term Implications on Society [68.8204255655161]
We take a closer look at AI fairness and analyze how lack of AI fairness can lead to deepening of biases over time.
We discuss how biased models can lead to more negative real-world outcomes for certain groups.
If the issues persist, they could be reinforced by interactions with other risks and have severe implications on society in the form of social unrest.
arXiv Detail & Related papers (2023-04-16T11:22:59Z) - Cybertrust: From Explainable to Actionable and Interpretable AI (AI2) [58.981120701284816]
Actionable and Interpretable AI (AI2) will incorporate explicit quantifications and visualizations of user confidence in AI recommendations.
It will allow examining and testing of AI system predictions to establish a basis for trust in the systems' decision making.
arXiv Detail & Related papers (2022-01-26T18:53:09Z) - Making AI 'Smart': Bridging AI and Cognitive Science [0.0]
With the integration of cognitive science, the 'artificial' characteristic of Artificial Intelligence might soon be replaced with'smart'
This will help develop more powerful AI systems and simultaneously gives us a better understanding of how the human brain works.
We argue that the possibility of AI taking over human civilization is low as developing such an advanced system requires a better understanding of the human brain first.
arXiv Detail & Related papers (2021-12-31T09:30:44Z) - Trustworthy AI: A Computational Perspective [54.80482955088197]
We focus on six of the most crucial dimensions in achieving trustworthy AI: (i) Safety & Robustness, (ii) Non-discrimination & Fairness, (iii) Explainability, (iv) Privacy, (v) Accountability & Auditability, and (vi) Environmental Well-Being.
For each dimension, we review the recent related technologies according to a taxonomy and summarize their applications in real-world systems.
arXiv Detail & Related papers (2021-07-12T14:21:46Z) - AI Failures: A Review of Underlying Issues [0.0]
We focus on AI failures on account of flaws in conceptualization, design and deployment.
We find that AI systems fail on account of omission and commission errors in the design of the AI system.
An AI system is quite likely to fail in situations where, in effect, it is called upon to deliver moral judgments.
arXiv Detail & Related papers (2020-07-18T15:31:29Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.